Particle recognition device

ABSTRACT

An image input section  1  obtains a halftone image IG of a to-be-measured particle group. A binarization section  2  binarizes the halftone image IT to obtain a binary image IB. A distance transform section  3  performs distance transform for the binary image IB to obtain a distance-transformed image ID. In this case, the particle nucleus extraction section  4  obtains particle nucleus candidates from the distance-transformed image ID and extracts a particle nucleus on the basis of the distance between the particle nucleus candidates and a separation parameter PS to obtain a particle nucleus image IC. A particle expansion section  5  performs particle expansion processing for the particle nucleus image IC and distance-transformed image ID to obtain a particle-separated image IS. In this case, the particle expansion section  5  performs particle expansion processing for the particle nucleus in the particle nucleus image IC along the value of distance transform to obtain the particle-separated image IS. A particle is recognized from the particle-separated image IS. In this way, a particle is recognized at a high speed and high accuracy.

1. TECHNICAL FIELD

The present invention relates to a particle recognition apparatus forseparating a particle from a halftone image of a to-be-measured particlegroup represented by a fertilizer, exploded splinters, or vegetables orfruits and recognizing the particle of an element and, moreparticularly, to a particle recognition apparatus used to measure aparticle size distribution or analyze the shape of a pore in a metal,mineral, or fiber.

2. BACKGROUND ART

As particle recognition apparatuses of this type, conventionally, thereare particle recognition apparatuses using labeling or particlerecognition apparatuses using distance transform.

[Particle Recognition Apparatus Using Labeling (Prior Art 1)]

A particle recognition apparatus using labeling recognizes a particlewith the following procedures.

(1): A particle group to be measured is photographed to obtain ahalftone image.

(2): The halftone image obtained in (1) is binarized (“0”, “1”) toobtain a binary image (FIG. 11(a)).

(3): The binary image obtained in (2) is labeled to obtain a label image(FIG. 11(b)).

(4): Each label ({circle around (1)} to {circle around (6)}) isrecognized as one particle.

[Particle Recognition Apparatus Using Distance Transform (Prior Art 2)]

A particle recognition apparatus using distance transform recognizes aparticle with the following procedures.

(1): A particle group to be measured is photographed to obtain ahalftone image.

(2): The halftone image obtained in (1) is binarized (“0”, “1”) toobtain a binary image.

(3): The binary image obtained in (2) is subjected to distance transformto obtain a distance-transformed image (FIG. 12(a)).

(4): An image Dk obtained by extracting pixels with values equal to orlarger than a threshold value k from the distance-transformed imageobtained in (3) to obtain a resultant image line Ok (FIG. 13(a)).

(5): The resultant image line Ok obtained in (4) is subjected toexclusive expansion to obtain an image E (FIG. 13(b)).

(6): A cuttable image C (FIG. 13(d)), uncuttable image I (FIG. 13(e)),and new image N (FIG. 13(f)) are classified from an image D_(k−1) (FIG.13(c)).

(7): The image C and image E are ANDed to obtain an image A (FIG.13(g)).

(8): The image N is smoothed to obtain an image N′ (FIG. 13(h)).

(9): The image A, image I, and image N′ are ORed to obtain an imageO_(k−1) (FIG. 13(i)).

(10): Steps (5) to (9) are repeated while decrementing the value k to 1,thereby obtaining a particle-separated image.

(11): The particle-separated image obtained in (10) is labeled to obtaina label image (FIG. 12(b)).

(12):: Each label ({circle around (1)} to {circle around (7)}) isrecognized as one particle.

Note that the particle recognition technique using distance transform isdisclosed in, e.g., Japanese Patent Laid-Open No. 62-211783 (imageprocessing apparatus).

3. DISCLOSURE OF INVENTION Problem to be Solved by the Invention

However, according to such a conventional particle recognitionapparatus, in the particle recognition apparatus (prior art 1) usinglabeling, if a plurality of particles in contact with each other arebinarized into the binary image, the plurality of particles in contactare recognized as one particle, resulting in low particle recognitionaccuracy.

More specifically, in particle recognition using an image, generally,the halftone image of particles is often unclear because of the particlephotographing environment, Additionally, in the binary image obtained bybinarization, a plurality of particles are often binarized in contactwith each other. However, the particle recognition apparatus usinglabeling often recognizes particles in contact with each other as oneparticle. This often affects the particle recognition result.

If the binarization level is raised to avoid this problem, particles maybe recognized as particles with much smaller sizes, or small particlesmay disappear.

On the other hand, in the particle recognition apparatus (prior art 2)using distance transform, even when a plurality of particles arebinarized into a binary image in contact with each other, they can berecognized as the plurality of particles, respectively. This allowsaccurate particle recognition. However, since this apparatus usesexclusive expansion processing in separating particles, a phenomenonoccurs in which the shape of a separated particle becomes different fromthe original particle shape. Hence, it is difficult to use thisapparatus for the application purpose such as pore shape analysis of ametal or mineral. In addition, this apparatus must repeatedly performnot only calculation for distance transform but also calculation fordegeneration for image separation, labeling, exclusive expansion, OR,and AND a plurality of number of times, and the calculation amount isenormous. This takes a long processing time, so this apparatus can beintroduced only in an environment with a lenient time limitation.

In a chemical plant for a fertilizer or chemical material, the particlesize distribution of a particle group being carried on a belt ismeasured, and the particle size distribution measurement result is usedas feedback information to control the charging amount of a material orwater. For this purpose, the particle recognition result must be quicklyobtained, and the processing time of particle size distributionmeasurement is also required to be shorter. In a chemical plant for afertilizer or chemical material, the processing time taken for particlesize distribution measurement must be several sec or shorter. Because ofthe problem of accuracy, prior art 1 is difficult to use. Prior art 2cannot be used because it takes several min for particle sizedistribution measurement due to the enormous calculation amount.

Means of Solution to the Problem

The present invention has been made to solve the above problem, and hasas its object to provide a particle recognition apparatus capable ofrecognizing a particle at a high speed and high accuracy.

In order to achieve the above object, the first invention comprisesimage input means (1) for obtaining a halftone image (IG) of a particlegroup to be measured, binarization means (2) for binarizing the halftoneimage (IG) obtained by the image input means(1) to obtain a binary image(IB), distance transform means (3) for performing distance transform forthe binary image (IB) binarized by the binarization means (2) to obtaina distance-transformed image (ID), particle nucleus extraction means (4)for performing particle nucleus extraction processing for thedistance-transformed image (ID) obtained by the distance transform means(3) to obtain a particle nucleus image (IC), and particle expansionmeans (5) for performing particle expansion processing for the particlenucleus image (IC) obtained by the particle nucleus extraction means (4)and the distance-transformed image (ID) obtained by the distancetransform means (3) to obtain a particle-separated image (IS).

According to this invention, the halftone image (IG) of the particlegroup to be measured is binarized into the binary image (IB), the binaryimage (IB) is subjected to distance transform to obtain thedistance-transformed image (ID), and the distance-transformed image (ID)is subjected to particle nucleus extraction processing to obtain theparticle nucleus image (IC), and the particle nucleus image (IC) anddistance-transformed image (ID) are subjected to particle expansionprocessing to obtain the particle-separated image (IS).

According to the second invention, in the first invention, particlenucleus candidates are obtained from the distance-transformed image(ID), and a particle nucleus is extracted on the basis of the distancebetween the particle nucleus candidates.

According to this invention, the particle nucleus candidates areobtained from the distance-transformed image (ID), the particle nucleusis extracted on the basis of the distance between the particle nucleuscandidates to obtain the particle nucleus image (IC), and the particlenucleus image (IC) and distance-transformed image (ID) are subjected toparticle expansion processing to obtain the particle-separated image(IS).

According to the third invention, in the first invention, parametersetting means for setting a separation parameter (PS) that defines adegree of extraction of the particle nucleus in the particle nucleusextraction processing is provided, and particle nucleus candidates areobtained from the distance-transformed image (ID), and a particlenucleus is extracted on the basis of the distance between the particlenucleus candidates and the separation parameter (PS).

According to this invention, the particle nucleus is extracted on thebasis of the distance between the particle nucleus candidates andseparation parameter (PS) to obtain the particle nucleus image (IC), andthe particle nucleus image (IC) and distance-transformed image (ID) aresubjected to particle expansion processing to obtain theparticle-separated image (IS). In this case, the degree of extraction ofthe particle nuclei (the degree of separation of particles) can beadjusted by changing the separation parameter (PS).

According to the fourth invention, in the second invention, a firstintermediate image (IT1) is obtained by adding a value near 3×3 pixelsto the distance-transformed image (ID), a second intermediate image(IT2) is obtained by performing filter processing for the firstintermediate image (IT1) to output a maximum value near the 3×3 pixels,and a third intermediate image (IT3) representing the particle nucleuscandidate is obtained by masking the distance-transformed image (ID)using an image obtained by extracting isoplethic points from the firstand second intermediate images (IT1, IT2).

According to this invention, the value near the 3×3 pixels is added tothe distance-transformed image (ID) to obtain the first intermediateimage (IT1), the first intermediate image (IT1) is subjected to filterprocessing to output the maximum value near the 3×3 pixels to obtain thesecond intermediate image (IT2), and the distance-transformed image (ID)is masked using an image obtained by extracting isoplethic points fromthe first and second intermediate images (IT1, IT2) to obtain the thirdintermediate image (IT3) representing the particle nucleus candidate.The particle nucleus is extracted on the basis of the distance betweenthe particle nucleus candidates in the third intermediate image (IT3) toobtain the particle nucleus image (IC).

According to the fifth invention, in the third invention, a firstintermediate image (IT1) is obtained by adding a value near 3×3 pixelsto the distance-transformed image (ID), a second intermediate image(IT2) is obtained by performing filter processing for the firstintermediate image (IT1) to output a maximum value near the 3×3 pixels,and a third intermediate image (IT3) representing the particle nucleuscandidate is obtained by masking the distance-transformed image (ID)using an image obtained by extracting isoplethic points from the firstand second intermediate images (IT1, IT2).

According to this invention, the value near the 3×3 pixels is added tothe distance-transformed image (ID) to obtain the first intermediateimage (IT1), the first intermediate image (IT1) is subjected to filterprocessing to output the maximum value near the 3×3 pixels to obtain thesecond intermediate image (IT2), and the distance-transformed image (ID)is masked using an image obtained by extracting isoplethic points fromthe first and second intermediate images (IT1, IT2) to obtain the thirdintermediate image (IT3) representing the particle nucleus candidate.The particle nucleus is extracted on the basis of the distance betweenthe particle nucleus candidates in the third intermediate image (IT3)and the separation parameter (PS) to obtain the particle nucleus image(IC).

According to the sixth invention, in the fifth invention, a fourthintermediate image (IT4) is obtained by multiplying the thirdintermediate image (IT3) by the separation parameter (PS), a fifthintermediate image (IT5) is obtained by performing inverse distancetransform for the fourth intermediate image (IT4), a sixth intermediateimage (IT6) is obtained by labeling the fifth intermediate image (IT5),and a particle nucleus image (IC) is obtained by masking the sixthintermediate image (IT6) using the third intermediate image (IT3).

According to this invention, the third intermediate image (IT3) ismultiplied by the separation parameter (PS) to obtain the fourthintermediate image (IT4), the fourth intermediate image (IT4) issubjected to inverse distance transform to obtain the fifth intermediateimage (IT5), the fifth intermediate image (IT5) is labeled to obtain thesixth intermediate image (IT6), and the sixth intermediate image (IT6)is masked using the third intermediate image (IT3) to obtain theparticle nucleus image (IC).

According to the seventh invention, in the first to sixth inventions,particle size distribution calculation means (7) for obtaining a size ofeach particle from the particle-separated image (IS) obtained by theparticle expansion means (5) to calculate a particle size distributionis provided. According to the present invention, the size of eachparticle is obtained from the particle-separated image (IS) to calculatethe particle size distribution.

4. BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram showing the main part of a particlerecognition apparatus according to an embodiment of the presentinvention;

FIG. 2 shows a situation until a particle-separated image is obtainedfrom a binary image in the particle recognition apparatus;

FIG. 3 is a block diagram showing the internal arrangement of a particlenucleus extraction section;

FIG. 4 is a block diagram showing the internal arrangement of a particleexpansion section;

FIG. 5(a) is a photograph showing the particle image (binary image) of a6-mm spherical particle group, which is displayed on a display, FIG.5(b) is a photograph showing the particle separation result by themethod of prior art 1, which is displayed on the display; FIG. 5(c) is aphotograph showing the particle separation result by the method of priorart 2, which is displayed on the display; and FIG. 5(d) is a photographshowing the particle separation result by a method of the presentinvention, which is displayed on the display;

FIG. 6 is a view showing the processing time of each method;

FIG. 7(a) is a photograph showing the particle image (binary image) of afertilizer on a belt conveyor, which is displayed on a display, FIG.7(b) is a photograph showing the particle separation result by themethod of prior art 1, which is displayed on the display; FIG. 7(c) is aphotograph showing the particle separation result by the method of priorart 2, which is displayed on the display; and FIG. 7(d) is a photographshowing the particle separation result by a method of the presentinvention, which is displayed on the display;

FIG. 8 is a view showing the processing time of each method;

FIG. 9 is a block diagram of a particle recognition apparatus in which aparticle size distribution calculation section is added to thearrangement shown in FIG. 1;

FIG. 10 is a view showing a processing example (8×8) by the particlenucleus extraction section;

FIG. 11(a) is a view showing a binary image in the particle recognitionprocess by a particle recognition apparatus (prior art 1) usinglabeling; and FIG. 11(b) is a view showing a label image as the particlerecognition result;

FIG. 12(a) is a view showing a binary image in the particle recognitionprocess by a particle recognition apparatus (prior art 1) using distancetransform; and FIG. 12(b) is a view showing a label image as theparticle recognition result; and

FIG. 13 is a view for explaining the particle recognition process in theparticle recognition apparatus (prior art 2) using distance transform.

5. BEST MODE OF CARRYING OUT THE INVENTION

The present invention will be described below in detail on the basis ofan embodiment. FIG. 1 is a block diagram showing the main part of aparticle recognition apparatus according to an embodiment of the presentinvention. Referring to FIG. 1, reference numeral 1 denotes an imageinput section; 2, a binarization section; 3, a distance transformsection; 4, a particle nucleus extraction section; 5, a particleexpansion section; 6, a parameter setting section; and 7, a particlerecognition section.

The image input section 1 obtains a halftone image IG: IG(x,y) {x,y=0,1, . . . , N−1} of a photographed to-be-measured particle group havingN×N pixels.

The binarization section 2 obtains a binary image IB: IB (x,y) {x,y=0,1, . . . , N−1} from the halftone image IG and a predetermined thresholdvalue T using the following equation (FIG. 2(a)). $\begin{matrix}{{{IB}\left( {x,y} \right)} = \left\{ \begin{matrix}{{1\quad {IG}\quad \left( {x,y} \right)} \geq T} \\{{0\quad {IG}\quad \left( {x,y} \right)} < T}\end{matrix} \right.} & \text{[Equation~~1]}\end{matrix}$

The distance transform section 3 performs distance transform for thebinary image IB to obtain a distance-transformed image ID (FIG. 2(b)).In this case, distance transform is transform processing of giving, to apixel whose value is not “0”, the shortest distance to a pixel having avalue “0” as a value. Actually, after the image IB is copied to theimage ID, processing represented by the following equation is performedtwice by scanning.

ID(x,y)=min(ID (a,b)) {a=x−1 to x+1, b=y−1 to y+1} +1

The particle nucleus extraction section 4 obtains particle nucleuscandidates from the distance-transformed image ID and extracts aparticle nucleus on the basis of the distance between the particlenucleus candidates and a separation parameter PS, thereby obtaining aparticle nucleus image IC:

IC(x,y) {x,y=0, 1, . . . , N−1} (FIG. 2(c)).

The particle expansion section 5 receives the distance-transformed imageID and particle nucleus image IC and performs particle expansionprocessing for the particle nucleus in the particle nucleus image ICalong the value of distance transform, thereby obtaining aparticle-separated image IS: IS(x,y) {x,y=0, 1, . . . , N−1} (FIG.2(d)).

The parameter setting section 6 sets, for the particle nucleusextraction section 4, the separation parameter PS which defines thedegree of extraction (the degree of separation) in particle nucleusextraction processing.

FIG. 3 is a block diagram showing the internal arrangement of theparticle nucleus extraction section 4. The particle nucleus extractionsection 4 comprises an addition filter 4-1, maximum filter 4-2, firstmask filter 4-3, proportional filter 4-4, inverse distance transformsection 4-5, labeling section 4-6, and second mask filter 4-7.

The addition filter 4-1 adds a value near 3×3 pixels to thedistance-transformed image ID from the distance transform section 3 toobtain an intermediate image IT1: IT1(x,y) {x,y=0, 1, . . . , N−1} (FIG.10(b)). $\begin{matrix}{{{IT1}\left( {x,y} \right)} = {\underset{a = {x - 1}}{\sum\limits^{x + 1}}{\underset{b = {y - 1}}{\sum\limits^{y + 1}}{{ID}\left( {a,b} \right)}}}} & \text{[Equation~~2]}\end{matrix}$

The maximum filter 4-2 performs filter processing for the intermediateimage IT1 from the addition filter 4-1 to output the maximum value near3×3 pixels, thereby obtaining an intermediate image IT2: IT2 (x,y){x,y=0, 1, . . . , N−1} (FIG. 10(c)).

IT 2(x,y)=max(IT 1 (a,b)) {a=x−1 to x+1, b=y−1 to y+1}

The first mask filter 4-3 masks the distance-transformed image ID fromthe distance transform section 3 using an image obtained by extractingvertices (isoplethic points) from the intermediate images IT1 and IT2,thereby obtaining an intermediate image IT3: IT3 (x,y) {x,y=0, 1, . . ., N−1} representing a particle nucleus candidate (FIG. 10(d)). In thiscase, referring to FIG. 10(d), a region Sa represented by a pixel value“2” and regions Sb and Sc represented by a pixel value “1” are particlenucleus candidates. $\begin{matrix}{{{IT3}\left( {x,y} \right)} = \left\{ \begin{matrix}\left. {{ID}\left( {x,y} \right)}\leftarrow{{{IT1}\left( {x,y} \right)}=={{IT2}\left( {x,y} \right)}} \right. \\\left. 0\leftarrow{{{IT1}\left( {x,y} \right)}\text{!} = {{IT2}\left( {x,y} \right)}} \right.\end{matrix} \right.} & \text{[Equation~~3]}\end{matrix}$

In equations in this specification, “==” represents that the left-handmember and right-hand member equal, “!=” represents that the left-handmember and right-hand member do not equal, and “=” represents asubstitution of the value of the right-hand member into the variable ofthe left-hand member.

The proportional filter 4-4 multiplies the intermediate image IT3 by theseparation parameter PS from the parameter setting section 6 to obtainan intermediate image IT4: IT4 (x,y) {x,y =0, 1, . . . , N−1} (FIG.10(e)).

IT 4 (x, y)=PS×IT 3 (x, y)

The inverse distance transform section 4-5 performs processingrepresented by the following equation for the intermediate image IT4twice by scanning to perform inverse distance transform processing,thereby obtaining an intermediate image IT5: IT5(x,y) {x,y=0, 1, . . . ,N−1} (FIG. 10(f)). $\begin{matrix}{{{IT}\quad 5\left( {x,y} \right)} = \left\{ {\begin{matrix}\left. {{\max \left( {{IT}\quad 4\left( {a,b} \right)} \right)} - 1}\leftarrow{{\max \left( {{IT}\quad 4\left( {a,b} \right)} \right)} > 1} \right. \\\left. 0\leftarrow{\max\left( {{{IT}\quad 4\left( {a,b} \right)} \leq 1} \right.} \right.\end{matrix}\left( {{{\because\alpha} = {x - {1\quad {to}{\quad \quad}x} + 1}},{b = {y - {1\quad {to}{\quad \quad}y} + 1}}} \right)} \right.} & \text{[Equation~~4]}\end{matrix}$

The labeling section 4-6 labels pixels whose values are not “0” in theintermediate image IT5 to obtain an intermediate image IT6: IT6 (x,y){x,y=0, 1, . . . , N−1} (FIG. 10(g)). In this case, referring to FIG.10(g), label {circle around (1)} is given to an inverse distancetransform region S1 of a region Sa′ represented by a pixel value “3” inFIG. 10(e) and a region Sb′ close to the region Sa′, which isrepresented by a pixel value “1”,and label {circle around (2)} is givento an inverse distance transform region S2 of a region Sc′ at a positionseparated from the region Sa′ in FIG. 10(e), which is represented by apixel value “1”.

The second mask filter 4-7 masks the intermediate image IT6 using theintermediate image IT6 to obtain the particle nucleus image IC: IC(x,y){x,y=0, 1, . . . , N−1} (FIG. 10(h)). In this case, referring to FIG.10(h), the particle nucleus candidates Sa and Sb in FIG. 10(d) areextracted as one particle nucleus represented by label {circle around(1)}, and the particle nucleus candidate Sc is extracted as one particlenucleus represented by label {circle around (2)}. $\begin{matrix}{{{IC}\left( {x,y} \right)} = \left\{ \begin{matrix}\left. {{IT}\quad 6\left( {x,y} \right)}\leftarrow{{{IT}\quad 3\left( {x,y} \right)}==0} \right. \\{\left. 0\leftarrow{{IT}\quad 3\left( {x,y} \right)\text{!}} \right. = 0}\end{matrix} \right.} & \text{[Equation~~5]}\end{matrix}$

FIG. 4 is a block diagram showing the internal arrangement of theparticle expansion section 5. The particle expansion section 5 has aparticle skin addition section 5-1, expansion separation section 5-2,and loop control section 5-3.

The particle skin addition section 5-1 obtains the distance-transformedimage ID from the distance transform section 3 upon receiving a loopcount z from the loop control section 5-3. In addition, the particleskin addition section 5-1 obtains the particle nucleus image IC from theparticle nucleus extraction section 4 when the value z is the maximumvalue of distance transform, and otherwise, obtains an intermediateseparated image IL from the expansion separation section 5-2, and adds aportion having the value z in the distance-transformed image ID to theparticle nucleus image IC or intermediate separated image IL, therebygenerating a particle skin image IE. $\begin{matrix}{{{IE}\left( {x,y} \right)} = \left\{ \begin{matrix}\left. 1\leftarrow{{{ID}\left( {x,y} \right)}==k} \right. \\{{\left. {{IC}\left( {x,y} \right)}\leftarrow\left( {{{ID}\left( {x,y} \right)}\text{!} = k} \right) \right.\&}\left( {k=={\max ({ID})}} \right)} \\{{\left. {{IL}\left( {x,y} \right)}\leftarrow\left( {{{ID}\left( {x,y} \right)}\text{!} = k} \right) \right.\&}\left( {{k\text{!}} = {\max ({ID})}} \right)}\end{matrix} \right.} & \text{[Equation~~6]}\end{matrix}$

The expansion separation section 5-2 performs the following processingfor the particle skin image IE twice by scanning to attach a particlelabel to a particle skin and expands the particle to generate theintermediate separated image IL. Expansion separation is performed inthe following way.

(1): The particle skin image IE is copied to prepare the intermediateseparated image IL.

(2): The portion corresponding to IL(x,y)!=1 is kept unchanged.

(3): When IL (x,y)==1, and a value “−1” is present near 3×3 pixels, IL(x,y)=−1.

(4): When IL(x,y)==1, and one kind of label value (integer of 2 or more)is present near 3×3 pixels, the label value is given to IL (x,y).

(5): When IL (x,y)==1, and two or more kinds of label values are presentnear 3×3 pixels, IL (x,y)=−1.

The loop control section 5-3 is a control section for controlling aloop, which initializes the loop count z by the maximum value ofdistance transform. Every time the intermediate separated image IL isreceived from the expansion separation section 5-2, and when z is not 0,the value z is decremented by one and input to the particle skinaddition section 5-1, thereby continuing the loop. When z is 0, theparticle-separated image IS: IS(x,y) {x,y =0, 1, . . . , N−1} isgenerated from IE (x,y) and output to the particle recognition section7, thereby ending the loop.

The particle recognition section 7 receives the particle-separated imageIS from the particle expansion section 5 and recognizes each label asone particle. $\begin{matrix}{{{IS}\left( {x,y} \right)} = \left\{ \begin{matrix}\left. 0\leftarrow{{{IE}\left( {x,y} \right)}=={- 1}} \right. \\\left. {{IE}\left( {x,y} \right)}\leftarrow{{{IE}\left( {x,y} \right)}!={- 1}} \right.\end{matrix} \right.} & \text{[Equation~~7]}\end{matrix}$

According to this particle recognition apparatus, when particles areseparated from the halftone image of a particle group to be measured,and even when a plurality of particles are binarized in contact in thebinary image, the particles can be recognized as independent particles.Additionally, even when a particle largely deforms, it can be recognizedas one particle without any erroneous separation. In this case, when theappropriate separation parameter PS is set on the basis of the overlapcharacteristics of particles to be measured or a variation in imageinput accuracy and measurement environment, accurate particlerecognition can be performed. That is, the degree of extraction ofparticle nuclei (the degree of separation of particles) can be adjustedby adjusting the separation parameter PS, so accurate particlerecognition is enabled. Hence, even when the particle image is unclear,the particles can be more accurately separated using this particlerecognition apparatus, and the particle recognition accuracy increases.In addition, since particle expansion is performed for extractedparticle nuclei along the value of distance transform, the particles canbe separated while minimizing deformation of the original particleshapes, and more accurate particle recognition is enabled.

In this particle recognition apparatus, first, distance transform isperformed. After particle nuclei are extracted, the particle nuclei areexpanded a plurality of number of times by repetitive processing,thereby obtaining the final separated image. In prior art 2, thecalculation amount required for repetitive processing of one cycle isenormous because processing such as degeneration, labeling, exclusiveexpansion, OR, and AND are performed every cycle of repetitiveprocessing. However, the particle recognition apparatus of thisembodiment only expands particle nuclei every cycle of repetitiveprocessing. For this reason, the calculation amount is much smaller thanthat of prior art 2. As a result, the calculation amount of the entireprocessing is smaller than that of prior art 2.

The effect of the particle recognition apparatus of this embodiment wasverified by simulation. Two kinds of images were prepared as particleimages.

First, a 6-mm spherical particle group was photographed and binarized toobtain a particle image. The particle were recognized by the method ofprior art 1, the method of prior art 2, and the method of the presentinvention. The particle recognition results and times required forprocessing were compared. FIGS. 5(a) to 5(d) show the comparisonresults. FIG. 5(a) shows the particle image (binary image). FIG. 5(b)shows the particle recognition result by the method of prior art 1. FIG.5(c) shows the particle recognition result by the method of prior art 2.FIG. 5(d) shows the particle recognition apparatus result by the methodof the present invention.

These results reveal the following facts. The method of prior art 1allows high-speed processing. However, when a plurality of particles arebinarized in contact, the plurality of particles in contact arerecognized as one particle.

In the method of prior art 2, even when a plurality of particles arebinarized in contact, they are recognized as independent particles. Theparticles can be accurately recognized. However, as shown in FIG. 6,since the calculation amount is large, and processing takes a long time,this method can hardly be adapted to an application purpose with strictrestriction on time.

In the method of the present invention, even when a plurality ofparticles are binarized in contact, they are recognized as independentparticles. In addition, the calculation amount is reduced, and itbecomes ½ or less that of prior art 2.

Next, a fertilizer on a belt conveyor was photographed and binarized toobtain a particle image. The particles were recognized by the method ofprior art 1, the method of prior art 2, and the method of the presentinvention. The particle recognition results and times required forprocessing were compared. FIGS. 7(a) to 7(d) show the comparisonresults. FIG. 7(a) shows the particle image (binary image). FIG. 7(b)shows the particle recognition result by the method of prior art 1. FIG.7(c) shows the particle recognition result by the method of prior art 2.FIG. 7(d) shows the particle recognition apparatus result by the methodof the present invention.

These results reveal the following facts. In the method of prior art 1,the particle image has particles already binarized in contact. For thisreason, a plurality of particles in contact are recognized as oneparticle, so no correct particle recognition result is obtained.

In the method of prior art 2, separation is performed for a portionwhere a plurality of particles are binarized in contact. However, sincethe particles are separated using exclusive expansion, the shape of aseparated particle is considerably different from the original shape ofthe particle image. Additionally, in the method of prior art 2, thecalculation amount is large, resulting in a long processing time.

In the method of the present invention, expansion separation forparticles of a portion where a plurality of particles are binarized incontact is performed along the value of distance transform. For thisreason, the deformation between the shape of a separated particle andthe original shape of the particle image is small. This suggests thatparticle separation faithful to the original image is performed. As aconsequence, particles can be accurately recognized. In addition, thecalculation amount is decreased, and it becomes ½ or less that of priorart 2.

As is apparent from these results, the method of the present inventionallows separation of a particle with a shape closer to the originalparticle image even when a plurality of particles are in contact. Forthis reason, a more accurate particle recognition result can be obtainedas compared to prior art 1 or prior art 2.

Since the total calculation amount is decreased by decreasing thecalculation amount of one cycle of repetitive processing, the requiredcalculation amount is smaller than that of the method of prior art 2.Even when the calculation amount poses a problem in the method of priorart 2, the problem may be solved by introducing the method of thepresent invention.

Hence, when the method of the present invention is introduced to atarget plant such as a chemical plant to perform particle recognition,and the particle size distribution is calculated by obtaining the sizeof each particle from the resultant particle-separated image, accurateparticle size distribution measurement can be performed even when noclear particle image is obtained due to poor environment. In addition,particle size distribution measurement can be performed in a processingtime not to impede continuous control of the plant. That is, particlesize distribution measurement suitable for continuous operation controlof the plant can be performed in terms of systematic performanceincluding the accuracy and processing time. Hence, this method can beapplied to a plant where prior art 2 cannot be used. Consequently, theefficiency of control and operation of the plant can be increased, andcost of plant operation can be reduced.

FIG. 9 is a block diagram of a particle recognition apparatus added witha particle size distribution calculation section 8. The particle sizedistribution calculation section 8 obtains a diameter corresponding to acircle from the area of each particle on the basis of theparticle-separated image IS to obtain the diameter of the particle,converts the diameter to a weight ratio, and collects weight ratios,thereby obtaining a particle size distribution.

As has been described above, according to the present invention, in thefirst invention, a halftone image of a particle group to be measured isbinarized into a binary image, and the binary image is subjected todistance transform to obtain a distance-transformed image. Thisdistance-transformed image is subjected to particle nucleus extractionprocessing to obtain a particle nucleus image. The particle nucleusimage and distance-transformed image are subjected to particle expansionprocessing to obtain a particle-separated image. The particles can berecognized at a high speed and high accuracy. More specifically,particles overlapping each other can be separated, the separationaccuracy is higher than that of prior art 1, the processing load islighter than that of prior art 2, and the particles can be recognized ata high speed and high accuracy. Hence, particle recognition suitable forcontinuous operation control of a plant can be performed in terms ofsystematic performance including the accuracy and processing time.

In the second invention, since, in the first invention, particle nucleuscandidates are obtained from the distance-transformed image, andparticle nuclei are extracted on the basis of the particle nucleuscandidates, particle nucleus candidates close to each other are regardedas one particle nucleus, thereby increasing the particle nucleusextraction accuracy.

In the third invention, since, in the first invention, the parametersetting means for setting the separation parameter that defines thedegree of extraction of particle nuclei in particle nucleus extractionprocessing is provided, particle nucleus candidates are obtained fromthe distance-transformed image, and particle nuclei are extracted on thebasis of the distance between the particle nucleus candidates andseparation parameter, particle recognition suitable for an object to bemeasured can be performed by setting an appropriate separation parameterin accordance with the overlap characteristics of particles to bemeasured or a variation in image input accuracy and measurementenvironment.

In the fourth invention, since, in the second invention, the firstintermediate image is obtained by adding the value near 3×3 pixels tothe distance-transformed image, the second intermediate image isobtained by performing filter processing for the first intermediateimage to output the maximum value near the 3×3 pixels, and the thirdintermediate image representing a particle nucleus candidate is obtainedby masking the distance-transformed image using an image obtained byextracting isoplethic points from the first and second intermediateimages, the particle nucleus candidates can be reliably detected, andthe particle recognition accuracy is improved.

In the fifth invention, since, in the third invention, the firstintermediate image is obtained by adding the value near 3×3 pixels tothe distance-transformed image, the second intermediate image isobtained by performing filter processing for the first intermediateimage to output the maximum value near the 3×3 pixels, and the thirdintermediate image representing a particle nucleus candidate is obtainedby masking the distance-transformed image using an image obtained byextracting isoplethic points from the first and second intermediateimages, the particle nucleus candidates can be reliably detected, andthe particle recognition accuracy is improved.

In the sixth invention, since, in the fifth invention, the fourthintermediate image is obtained by multiplying the third intermediateimage by the separation parameter, the fifth intermediate image isobtained by performing inverse distance transform for the fourthintermediate image, the sixth intermediate image is obtained by labelingthe fifth intermediate image, and a particle nucleus image is obtainedby masking the sixth intermediate image using the third intermediateimage, particle recognition suitable for an object to be measured can beperformed by setting an appropriate separation parameter in accordancewith the overlap characteristics of particles to be measured or avariation in image input accuracy and measurement environment. Inaddition, the particle nuclei can be extracted at a high accuracy, andthe particle recognition accuracy is improved.

In the seventh invention, since in the first to sixth inventions, aparticle size distribution calculation means for calculating theparticle size distribution by obtaining the size of each particle fromthe particle-separated image obtained by the particle expansion means isprovided, the particle size distribution can be measured at a high speedand high accuracy. More specifically, particles overlapping each othercan be separated to measure the particle size distribution, theseparation accuracy is higher than that of prior art 1, the processingload is lighter than that of prior art 2, and the particle sizedistribution can be measured at a high speed and high accuracy. Hence,the method is suitable for continuous operation control of a plant interms of systematic performance including the accuracy and processingtime and can be applied to a plant where prior art 2 cannot be used.Consequently, the efficiency of control and operation of the plant canbe increased, and cost of plant operation can be reduced.

What is claimed is:
 1. A particle recognition apparatus comprising:image input means for obtaining a halftone image of a particle group tobe measured; binarization means for binarizing the halftone imageobtained by said image input means to obtain a binary image; distancetransform means for performing distance transform for the binary imagebinarized by said binarization means to obtain a distance-transformedimage; particle nucleus extraction means for performing particle nucleusextraction processing for the distance-transformed image obtained bysaid distance transform means to obtain a particle nucleus image; andparticle expansion means for performing particle expansion processing,from the particle nucleus image obtained by said particle nucleusextraction means, along a value of the distance transform of thedistance-transformed image obtained by said distance transform means, toobtain a particle-separated image.
 2. A particle recognition apparatusaccording to claim 1, wherein said particle nucleus extraction meansobtains particle nucleus candidates from the distance-transformed imageobtained by said distance transform means and extracts a particlenucleus on the basis of the distance between the particle nucleuscandidates.
 3. A particle recognition apparatus according to claim 1,further comprising: parameter setting means for setting a separationparameter that defines a degree of extraction of the particle nucleus inthe particle nucleus extraction processing, and said particle nucleusextraction means obtains particle nucleus candidates from thedistance-transformed image obtained by said distance transform means andextracts a particle nucleus on the basis of the distance between theparticle nucleus candidates and the separation parameter.
 4. A particlerecognition apparatus according to claim 2, wherein said particlenucleus extraction means obtains a first intermediate image by adding avalue near 3×3 pixels to the distance-transformed image obtained by saiddistance transform means, obtains a second intermediate image byperforming filter processing for the first intermediate image to outputa maximum value near the 3×3 pixels, and obtains a third intermediateimage representing the particle nucleus candidate by masking thedistance-transformed image using an image obtained by extractingisoplethic points from the first and second intermediate images.
 5. Aparticle recognition apparatus according to claim 3, wherein particlenucleus extraction means obtains a first intermediate image by adding avalue near 3×3 pixels to the distance-transformed image obtained by saiddistance transform means, obtains a second intermediate image byperforming filter processing for the first intermediate image to outputa maximum value near the 3×3 pixels, and obtains a third intermediateimage representing the particle nucleus candidate by masking thedistance-transformed image using an image obtained by extractingisoplethic points from the first and second intermediate images.
 6. Aparticle recognition apparatus according to claim 5, wherein saidparticle nucleus extraction means obtains a fourth intermediate image bymultiplying the third intermediate image by the separation parameter,obtains a firth intermediate image by performing inverse distancetransform for the fourth intermediate image, obtains a sixthintermediate image by labeling the fifth intermediate image, and obtainsa particle nucleus image by masking the sixth intermediate image usingthe third intermediate image.
 7. A particle recognition apparatusaccording to claim 1, further comprising particle size distributioncalculation means for obtaining a size of each particle from theparticle-separated image obtained by said particle expansion means tocalculate a particle size distribution.
 8. A particle recognitionapparatus comprising: an image input section to generate a halftoneimage of a particle group to be measured; a binarization section tobinarize the halftone image generated by the image input section togenerate a binary image; a distance transform section to performdistance transform for the binary image binarized by the binarizationsection and to generate a distance-transformed image based on thedistance transform; a particle nucleus extraction section to extractparticle nucleus based on the distance-transformed image and to generatea particle nucleus image based on the extracted particle nucleus; and aparticle expansion section to perform particle expansion processing forthe extracted particle nucleus based on a value of the distancetransform to generate a particle-separated image.
 9. A particlerecognition apparatus according to claim 8, wherein the particle nucleusextraction section obtains particle nucleus candidates from thedistance-transformed image and extracts a particle nucleus on a basis ofa distance between the particle nucleus candidates.
 10. A particlerecognition apparatus according to claim 8, further comprising: aparameter setting section to set a separation parameter that defines adegree of extraction of the particle nucleus in the particle nucleusextraction processing, wherein the particle nucleus extraction sectionobtains particle nucleus candidates from the distance-transformed imageand extracts a particle nucleus on a basis of a distance between theparticle nucleus candidates and the separation parameter.
 11. A particlerecognition apparatus according to claim 9, wherein the particle nucleusextraction section obtains a first intermediate image by adding a valuenear 3×3 pixels to the distance-transformed image, obtains a secondintermediate image by performing filter processing for the firstintermediate image to output a maximum value near the 3×3 pixels, andobtains a third intermediate image representing the particle nucleuscandidate by masking the distance-transformed image using an imageobtained by extracting isoplethic points from the first and secondintermediate images.
 12. A particle recognition apparatus according toclaim 10, wherein the particle nucleus extraction section obtains afirst intermediate image by adding a value near 3×3 pixels to thedistance-transformed image, obtains a second intermediate image byperforming filter processing for the first intermediate image to outputa maximum value near the 3×3 pixels, and obtains a third intermediateimage representing the particle nucleus candidate by masking thedistance-transformed image using an image obtained by extractingisoplethic points from the first and second intermediate images.
 13. Aparticle recognition apparatus according to claim 12, wherein theparticle nucleus extraction section obtains a fourth intermediate imageby multiplying the third intermediate image by the separation parameter,obtains a firth intermediate image by performing inverse distancetransform for the fourth intermediate image, obtains a sixthintermediate image by labeling the fifth intermediate image, and obtainsa particle nucleus image by masking the sixth intermediate image usingthe third intermediate image.
 14. A particle recognition apparatusaccording to claim 8, further comprising a particle size distributioncalculation section to obtain a size of each particle from theparticle-separated image obtained by said particle expansion section tocalculate a particle size distribution.